Applying deep learning algorithms to the task of clearing space junk

EPFL researchers are at the forefront of developing some of the cutting-edge technology for the European Space Agency's first mission to remove space debris from orbit. How do you measure the pose – that is the 3D rotation and 3D translation – of a piece of space junk so that a grasping satellite can capture it in real time in order to successfully remove it from Earth's orbit? What role will deep learning algorithms play? And, what is real time in space? These are some of the questions being tackled in a ground-breaking project, led by ClearSpace, a spin-off from the EPFL Space Center (eSpace), to develop technologies to capture and deorbit space debris. With more than 34,000 pieces of junk orbiting around the Earth, their removal is becoming a matter of safety.